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Technical Paper

Improving the Reliability of Squeak & Rattle Test

2005-05-16
2005-01-2539
The laboratory test method commonly known as “random vibration” is almost always used for Squeak & Rattle testing in today's automotive applications due to its obvious advantages: the convenience in simulating the real road input, the relatively low cost, and efficiency in obtaining the desired test results. Typically, Loudness N10 is used to evaluate the Squeak & Rattle (S&R) performance. However, due to the nature of random distribution of the excitation input, the repeatability of the loudness N10 measurements may vary significantly. This variation imposes a significant challenge when one is searching for a fine design improvement solution in minimizing S&R noise, such as a six-sigma study. This study intends to investigate (1) the range of the variations of random vibration control method as an excitation input with a given PSD, (2) the possibility of using an alternate control method (“time-history replication”) to produce the vibration of a given PSD for a S&R evaluation.
Technical Paper

Analytical Predictions and Correlation With Physical Tests for Potential Buzz, Squeak, and Rattle Regions in a Cockpit Assembly

2004-03-08
2004-01-0393
The perceived interior noise has been one of the major driving factors in the design of automotive interior assemblies. Buzz, Squeak and Rattle (BSR) issues are one of the major contributors toward the perceived quality in a vehicle. Traditionally BSR issues have been identified and rectified through extensive hardware testing. In order to reduce the product development cycle and minimize the number of costly hardware builds, however, one must rely on engineering analysis and simulation upfront in the design cycle. In this paper, an analytical and experimental study to identify potential BSR locations in a cockpit assembly is presented. The analytical investigation utilizes a novel and practical methodology, implemented in the software tool Nhance.BSR, for identification and ranking of potential BSR issues. The emphasis here is to evaluate the software for the BSR predictions and the identification of modeling issues, rather than to evaluate the cockpit design itself for BSR issues.
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